File size: 5,353 Bytes
3035eb3
 
a20b586
3035eb3
6f94c2e
3035eb3
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
6f94c2e
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
a20b586
6f94c2e
 
 
 
 
 
 
 
3035eb3
 
a20b586
3035eb3
 
 
 
 
 
a20b586
3035eb3
 
 
6babdb7
a20b586
 
3035eb3
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
a20b586
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
3035eb3
 
 
 
 
 
a20b586
 
 
 
44418a4
 
 
 
 
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
---
license: apache-2.0
language: ca
tags:
- catalan
datasets:
- catalonia_independence
metrics:
- accuracy
model-index:
- name: roberta-base-ca-finetuned-mnli
  results:
  - task:
      name: Text Classification
      type: text-classification
    dataset:
      name: catalonia_independence
      type: catalonia_independence
      args: catalan
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.7611940298507462
  - task:
      type: text-classification
      name: Text Classification
    dataset:
      name: catalonia_independence
      type: catalonia_independence
      config: catalan
      split: test
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.7208955223880597
      verified: true
    - name: Precision Macro
      type: precision
      value: 0.7532458247651523
      verified: true
    - name: Precision Micro
      type: precision
      value: 0.7208955223880597
      verified: true
    - name: Precision Weighted
      type: precision
      value: 0.7367396361532118
      verified: true
    - name: Recall Macro
      type: recall
      value: 0.6880645531209203
      verified: true
    - name: Recall Micro
      type: recall
      value: 0.7208955223880597
      verified: true
    - name: Recall Weighted
      type: recall
      value: 0.7208955223880597
      verified: true
    - name: F1 Macro
      type: f1
      value: 0.7013044744309381
      verified: true
    - name: F1 Micro
      type: f1
      value: 0.7208955223880597
      verified: true
    - name: F1 Weighted
      type: f1
      value: 0.713640086434487
      verified: true
    - name: loss
      type: loss
      value: 0.6895929574966431
      verified: true
widget:
- text: "Puigdemont, a l'estat espanyol: Quatre anys despr\xE9s, ens hem guanyat el\
    \ dret a dir prou"
- text: "Llarena demana la detenci\xF3 de Com\xEDn i Ponsat\xED aprofitant que s\xF3\
    n a It\xE0lia amb Puigdemont"
- text: "Assegura l'expert que en un 46% els catalans s'inclouen dins del que es denomina\
    \ com el doble sentiment identitari. \xC9s a dir, se senten tant catalans com\
    \ espanyols. 1 de cada cinc, en canvi, t\xE9 un sentiment excloent, nom\xE9s se\
    \ senten catalans, i un 4% sol espanyol."
---

# roberta-base-ca-finetuned-catalonia-independence-detector

This model is a fine-tuned version of [BSC-TeMU/roberta-base-ca](https://huggingface.co/BSC-TeMU/roberta-base-ca) on the catalonia_independence dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6065
- Accuracy: 0.7612

<details>

## Training and evaluation data

The data was collected over 12 days during February and March of 2019 from tweets posted in Barcelona, and during September of 2018 from tweets posted in the town of Terrassa, Catalonia.

Each corpus is annotated with three classes: AGAINST, FAVOR and NEUTRAL, which express the stance towards the target - independence of Catalonia.

## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 2e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 1.0   | 377  | 0.6311          | 0.7453   |
| 0.7393        | 2.0   | 754  | 0.6065          | 0.7612   |
| 0.5019        | 3.0   | 1131 | 0.6340          | 0.7547   |
| 0.3837        | 4.0   | 1508 | 0.6777          | 0.7597   |
| 0.3837        | 5.0   | 1885 | 0.7232          | 0.7582   |


</details>

### Model in action 🚀

Fast usage with **pipelines**:

```python

from transformers import pipeline

model_path = "JonatanGk/roberta-base-ca-finetuned-catalonia-independence-detector"
independence_analysis = pipeline("text-classification", model=model_path, tokenizer=model_path)

independence_analysis(
    "Assegura l'expert que en un 46% els catalans s'inclouen dins del que es denomina com el doble sentiment identitari. És a dir, se senten tant catalans com espanyols. 1 de cada cinc, en canvi, té un sentiment excloent, només se senten catalans, i un 4% sol espanyol."
    )
# Output:
[{'label': 'AGAINST', 'score': 0.7457581758499146}]

independence_analysis(
    "Llarena demana la detenció de Comín i Ponsatí aprofitant que són a Itàlia amb Puigdemont"
    )
# Output:
[{'label': 'NEUTRAL', 'score': 0.7436802983283997}] 
    
independence_analysis(
    "Puigdemont, a l'estat espanyol: Quatre anys després, ens hem guanyat el dret a dir prou"
    )
# Output:
[{'label': 'FAVOR', 'score': 0.9040119647979736}]


```

[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/JonatanGk/Shared-Colab/blob/master/Catalonia_independence_Detector_(CATALAN).ipynb#scrollTo=j29NHJtOyAVU)


### Framework versions

- Transformers 4.11.3
- Pytorch 1.9.0+cu111
- Datasets 1.12.1
- Tokenizers 0.10.3


## Citation

Thx to HF.co & [@lewtun](https://github.com/lewtun) for Dataset ;)

> Special thx to [Manuel Romero/@mrm8488](https://huggingface.co/mrm8488) as my mentor & R.C.

> Created by [Jonatan Luna](https://JonatanGk.github.io) | [LinkedIn](https://www.linkedin.com/in/JonatanGk/)